Skalar has raised €12 million through its pre-seed and seed financing rounds to expand an AI-first tax advisory firm designed to address Germany’s growing shortage of tax consultants. Headline led the financing, with participation from futurepresent, QED Investors, Repeat Ventures, MS&AD Ventures, Foreword Fund, and several angel investors.
The company plans to use the funding to automate additional tax advisory processes, develop its AI technology, expand its services, and grow its team.
Skalar is building a tax consultancy that has incorporated artificial intelligence into its operating model from the beginning. Rather than adding AI tools to a traditional firm, the company is designing its workflows around AI agents that handle routine and repetitive assignments.
Skalar’s tax professionals remain responsible for areas requiring judgment, accountability, interpretation, and direct client advice. The company believes this combination can increase the number of clients each professional can support without reducing the quality of service.
The financing comes as Germany faces a growing shortage of tax advisors. According to Skalar, nearly one-third of German tax consultants are over the age of 61, raising concerns about an approaching wave of retirements across the profession.
Many existing firms are already struggling to accept additional mandates because of limited capacity. This has made it increasingly difficult for companies, particularly small and midsized businesses, to access responsive and high-quality tax advice.
Skalar aims to address the shortage by automating administrative and routine tax processes that traditionally require substantial amounts of manual work.
AI agents can support tasks such as collecting and organizing documents, checking information, preparing workflows, identifying missing data, and assisting with recurring compliance processes.
By reducing the time tax experts spend on these activities, Skalar intends to allow them to focus on complex tax questions, client relationships, strategic guidance, and decisions that require professional judgment.
The company said demand for its model has emerged quickly. Skalar received more than 1,000 inquiries during its first three months of operation.
This initial interest indicates that businesses are looking for alternatives to conventional tax advisory models, particularly as established firms face capacity constraints and growing workloads.
Skalar has assembled a team of more than 25 employees within a matter of months. The new funding will support further hiring across tax advisory, software engineering, artificial intelligence, operations, and customer-facing roles.
The company’s model reflects a broader shift in professional services toward combining licensed or highly trained experts with software automation.
Tax consulting is particularly suited to this approach because firms manage large volumes of documents, repetitive workflows, deadlines, and rules-based processes. However, the sector also requires experienced professionals to interpret regulations, take responsibility for advice, and understand the specific circumstances of each client.
Skalar is seeking to preserve that human expertise while using AI to improve the speed and capacity of the underlying operation.
The company believes an AI-first approach can also create a more consistent client experience by making tax information easier to access, reducing delays, and providing greater transparency into ongoing work.
The €12 million in financing will allow Skalar to continue developing its technology and automate more of the processes involved in serving companies.
Skalar also plans to expand its workforce as it responds to its early pipeline of prospective clients and builds the operational infrastructure needed to support a larger number of mandates.
The company’s long-term goal is to rebuild the traditional tax consultancy model around technology while ensuring qualified tax professionals continue to oversee the work and provide advice where human responsibility and judgment are essential.
